Seasonally dry tropical forests are distributed across Latin America and the Caribbean and are highly threatened, with less than 10% of their original extent remaining in many countries. Using 835 inventories covering 4660 species of woody plants, we show marked floristic turnover among inventories and regions, which may be higher than in other neotropical biomes, such as savanna. Such high floristic turnover indicates that numerous conservation areas across many countries will be needed to protect the full diversity of tropical dry forests. Our results provide a scientific framework within which national decision-makers can contextualize the floristic significance of their dry forest at a regional and continental scale.

We investigated the use of full-range (400–2,500 nm) hyperspectral data obtained by sampling foliar reflectances to discriminate 46 plant species in a tropical wetland in Jamaica. A total of 47 spectral variables, including derivative spectra, spectral vegetation indices, spectral position variables, normalized spectra and spectral absorption features, were used for classifying the 46 species. The Mann–Whitney U-test, paired one-way ANOVA, principal component analysis (PCA), random forest (RF) and a wrapper approach with a support vector machine were used as feature selection methods. Linear discriminant analysis (LDA), an artificial neural network (ANN) and a generalized linear model fitted with elastic net penalties (GLMnet) were then used for species separation. For comparison, the RF classifier (denoted as RFa) was also used to separate the species by using all reflectance spectra and spectral indices, respectively, without applying any feature selection. The RFa classifier was able to achieve 91.8% and 84.8% accuracy with importance-ranked spectral indices and reflectance spectra, respectively. The GLMnet classifier produced the lowest overall accuracies for feature-selected reflectance spectra data (52–77%) when compared with the LDA and ANN methods. However, when feature-selected spectral indices were used, the GLMnet produced overall accuracies ranging from 79 to 88%, which were the highest among the three classifiers that used feature-selected data. A total of 12 species recorded a 100% producer accuracy, but with spectral indices, and an additional 8 species had perfect producer accuracies, regardless of the input features. The results of this study suggest that the GLMnet classifier can be used, particularly on feature-selected spectral indices, to discern vegetation in wetlands. However, it might be more efficient to use RFa without feature-selected variables, especially for spectral indices.

Tropical dry forests occupy more area and are more endangered than rainforests, yet their regeneration ecology has received less study and is consequently poorly understood. We recorded the flowering and fruiting phenology of a tropical dry forest in Jamaica over a period of 26 mo within ten 15 × 15‐m plots. Community‐wide recruitment reached a maximum in the wet season, whereas no recruitment occurred during the dry season. We observed a unimodal peak in rainfall and fruit production, and the periodicity and intensity of seed production were significantly correlated with rainfall seasonality (the optimal time for germination). Flowering at the community and system levels lagged behind a significant increase and subsequent decrease in rainfall by 7 and 3 mo, respectively, indicating that the dominant factor controlling flowering periodicity is the passage of the major (4‐mo long) rainy season and changes in soil moisture conditions. Fruiting lagged behind flowering by 2 mo and a significant increase in fruiting occurred 2 mo prior to a significant increase in rainfall. At the population level, a correspondence analysis identified a major dichotomy in the patterns of flowering and fruiting between species and indicated two broad species groups based on their time of peak fruiting and the number of times they were in fruit. These were either individuals which were usually in peak fruit 1–2 mo prior to the start of the major rainy season or those that were in fruit more or less continuously throughout the year with no peak fruiting time. This study supports the view that seasonal variation in rainfall and hence soil water availability constitutes both the proximate and the ultimate cause of flowering periodicity in tropical dry forests.

Invasive species have caused widespread economic and environmental disruption, which have been widely studied. However, their potential benefits have received much less attention. If invasive species contribute to livelihoods, their eradication may negatively impact wellbeing. Failing to value these benefits may lead to an undervaluation of invaded ecosystems. We assess the potential economic benefits of an invasive species within an artisanal fishery in Jamaica. We monitored catches over 259 fisherman-days, and conducted 45 semi-structured interviews, with 76 fishermen. We show that the invasive Australian Red Claw crayfish (Cherax quadricarinatus) is an important source of income for fishermen within the Black River Lower Morass of Jamaica and supplement incomes during periods when native shrimp (Macrobrachium spp.) catches decline. We also show that full-time fishermen and those who have no alternative occupations expend the greatest fishing effort. We use the intra-annual variation of fishermen's harvest effort between seasons (when catch per unit effort changes) as a proxy for dependence. Using this measure, we found that the least wealthy appear to be the most dependent on fishing, and consequently benefit the most from the invasive crayfish. Our results demonstrate the importance of considering the potential benefits of invasive species within integrated landscape management